Junior QA Engineer

About Role

As an ideal candidate for the Junior QA Engineer (ETL & Data Testing) position, you have a foundational understanding of ETL processes and a keen interest in ensuring data quality and integrity through structured testing practices. You bring a blend of analytical thinking and a methodical approach, enabling you to support the execution of effective testing strategies for data integration projects. From a technical perspective, you have exposure to ETL tools and frameworks and understand how data flows through pipelines. You are eager to build your expertise in validating data transformations, integrations, and load processes. You have a basic understanding of Agile methodologies, test execution, and defect tracking, and you actively participate in team discussions and status updates.

What you’ll bring

• 2–4 years of experience in software testing, preferably with exposure to data/ETL testing • Basic understanding of ETL processes and data pipelines

• Proficiency in SQL for data querying and validation

• Familiarity with Python, Selenium, and/or automation frameworks

• Exposure to GitHub and CI/CD pipelines

• Basic knowledge of Azure/cloud environments

• Understanding of data comparison and validation techniques

• Awareness of incremental data loads and data processing concepts

• Basic knowledge of Microsoft Fabric and Lakehouse vs Data Warehouse concepts

• Experienced in BI tools like Power BI

• Understanding of SDLC and STLC processes

• Familiarity with Agile methodology

• Open mindset with a willingness to learn new technologies, especially AI tools in QA

Education Qualification

Bachelor’s degree in computer science, IT, or related field

Skills- Testing, SQL, Python/ Selenium, ETL Testing, CI/CD, GitHub, Data Validation, Automation (basic), BI Tools

What you will do

• Assist in providing accurate updates on test progress and outcomes

• Support testing of BI reports for data accuracy and functionality

• Maintain and update tasks within workflows and provide daily status updates

• Ensure assigned quality assurance objectives are met before delivery

• Contribute to continuous improvement by identifying and addressing quality issues

• Develop and maintain basic automation scripts using Python for:

• Data comparison (source vs target) • Regression testing

• Data validation support

• Support integration of automation scripts into CI/CD pipelines

• Leverage AI tools (such as Cursor, Copilot, etc.) to improve productivity and testing efficiency